Intra- versus interpersonal emotion regulation: Associations with affect, relationship quality and closeness, and biological markers of stress.
Bibliographic record
Abstract
Past research has focused on emotion regulation (ER) as an intrapersonal endeavor (managing one's own emotions), leaving many questions unanswered about interpersonal emotion regulation (IER; receiving support from another person to regulate one's emotions). This study sought to understand the effects of two common IER strategies (corumination, codistraction) by comparing them with each other and their intrapersonal counterparts (rumination, distraction) on negative and positive affect, relationship quality and closeness, and biological stress responses (i.e., cortisol and salivary alpha-amylase [sAA]). Participants completed the Fast Friends paradigm and then privately recalled a stressful event. Participants were then randomized into one of four ER groups: rumination, distraction, corumination, or codistraction. Affect, relationship quality, closeness, cortisol, and sAA were measured throughout the study session and during a 40-min post-ER recovery period. Interestingly, the ER groups differed in affect and biological recovery from stress, but not in relationship quality or closeness. Specifically, distraction facilitated the greatest decline in negative affect during the ER induction, but negative affect decline was greater in rumination and corumination than in distraction during the recovery period. Additionally, both IER groups showed increased sAA levels during the ER induction, but sAA levels showed a greater decline in the IER than in intrapersonal ER groups during the recovery period. This study highlights the nuanced effects of intrapersonal versus IER strategies and thus informs approaches to modulate negative affect and biological markers of stress when facing stressful events. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".